Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

We present GaussianAvatar an efficient approach to creating realistic human avatars with
dynamic 3D appearances from a single video. We start by introducing animatable 3D …

Modeling animatable human avatars from RGB videos is a long-standing and challenging
problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent …

Whole-body pose estimation localizes the human body, hand, face, and foot keypoints in an
image. This task is challenging due to multi-scale body parts, fine-grained localization for …

We introduce TADA, a simple-yet-effective approach that takes textual descriptions and
produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be …

Real-time rendering of photorealistic and controllable human avatars stands as a
cornerstone in Computer Vision and Graphics. While recent advances in neural implicit …

This work addresses the problem of real-time rendering of photorealistic human body
avatars learned from multi-view videos. While the classical approaches to model and render …

Gaussian splatting has emerged as a powerful 3D representation that harnesses the
advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper we …

Creating expressive, diverse and high-quality 3D avatars from highly customized text
descriptions and pose guidance is a challenging task, due to the intricacy of modeling and …

We present SplattingAvatar a hybrid 3D representation of photorealistic human avatars with
Gaussian Splatting embedded on a triangle mesh which renders over 300 FPS on a modern …